• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.312-319
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• 2007

The solution of the power flow is one of the most important problems in electrical power systems. These traditional methods such as Gauss-Seidel method and Newton-Raphson (NR) method have had drawbacks up to now such as initial values, abnormal operating solutions and divergences in heavy loads. In order to overcome theses problems, the power flow solution incorporating genetic algorithm (GA) is introduced in this paper. General operator of genetic algorithm, arithmetic crossover, and non-uniform mutation operator of GA are suggested to solve the power flow problem. While abnormal solution cannot be obtained by a NR method, multiple power flow solution can be obtained by a GA method. With a heavy load, both normal solution and abnormal solution can be obtained by a proposed method. In this paper, a floating number representation instead of the binary number representation is introduced for accuracy. Simulation results have been compared with traditional methods.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.161-166
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• 2002

Low-tension cables have been increasingly used in recent years due to deep-sea developments and the advent of synthetic cables. In the case of low-tension cables, large displacements may happen due to relatively small restoring forces of tension and thus the effects of fluid and geometric non-linearities become predominant. In this study, three-dimensional (3-D) dynamic behavior of a towed low-tension cable with non-uniform characteristics is numerically analyzed by considering fluid and geometric non-linearities and bending stiffness. A Fortran program is developed by employing a finite difference method. In the algorithm, an implicit time integration and Newton-Raphson iteration are adopted. For the calculation of huge size of matrices, block tri-diagonal matrix method is applied, which is much faster than the well-known Gauss-Jordan method in two point boundary value problems. Some case studies are carried out and the results of numerical simulations are compared with a in-house program of WHOI Cable with good agreements.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.45-57
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• 1998

The purpose of this paper is to develop a neural network model in order to forecast flood inflow into the reservoir that has the nature of uncertainty and nonlinearity. The model has the features of multi-layered structure and parallel multi-connections. To develop the model. backpropagation learning algorithm was used with the Momentum and Levenberg-Marquardt techniques. The former technique uses gradient descent method and the later uses gradient descent and Gauss-Newton method respectively to solve the problems of local minima and for the speed of convergency. Used data for learning are continuous fixed real values of input as well as output to emulate the real physical aspects. after learning process. a reservoir inflows forecasting model at flood period was constructed. The data for learning were used to calibrate the developed model and the results were very satisfactory. applicability of the model to the Chungju Mlultipurpose Reservoir proved the availability of the developed model.

• Geophysics and Geophysical Exploration
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• v.10 no.2
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• pp.147-153
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• 2007

The conjugate gradient (CG) method is one of the most efficient algorithms for solving a linear system of equations. In addition to being used as a linear equation solver, it can be applied to a least-squares problem. When the CG method is applied to large-scale three-dimensional inversion of magnetotelluric data, two approaches have been pursued; one is the linear CG inversion in which each step of the Gauss-Newton iteration is incompletely solved using a truncated CG technique, and the other is referred to as the nonlinear CG inversion in which CG is directly applied to the minimization of objective functional for a nonlinear inverse problem. In each procedure we only need to compute the effect of the sensitivity matrix or its transpose multiplying an arbitrary vector, significantly reducing the computational requirements needed to do large-scale inversion.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.186-194
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• 2019

Deterministic optimization, commonly used to find the geophysical inverse solutions, have its limitation that it cannot find the proper solution since it might converge into the local minimum. One of the solutions to this problem is to use global optimization based on a stochastic approach, among which a large number of particle swarm optimization (PSO) applications have been introduced. In this paper, I developed a geophysical inversion algorithm applying PSO method for the layered-earth resistivity inversion of the small-loop electromagnetic (EM) survey data and carried out numerical inversion experiments on synthetic datasets. From the results, it is confirmed that the PSO inversion algorithm could increase the inversion success rate even when attempting the inversion of small-loop EM survey data from which it might be difficult to find a best solution by applying the Gauss-Newton inversion algorithm.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1145-1148
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• 2003

We show the mixed finite element method which induces solutions that has the same order of errors for both the gradient of the solution and the solution itself. The technique to construct an efficient reusable matrix is suggested. Two families of mixed finite element methods are introduced with an automatic generating technique for matrix with my order of basis. The generated matrix by this technique has more accurate values and is a sparse matrix. This new technique is applied to solve a minimal surface problem.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.7
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• pp.365-368
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• 2000

Traditionally, load flows have been calculated using the Gauss-Seidel and Newton-Raphson Method. DistFlow Method which is proposed by Wu and Baran is superior to the other two methods because it does not require the admittance matrix calculation to optimize the distribution system. This paper introduces a new alternative algorithm to the DistFlow Method which is slow and complex to find solutions as the number of lateral and sublateral increases. The proposed load flow method can construct System Jacobian easily. We can minimize the off-diagonal elements of the branch Jacobian and submatrices in the System Jacobian. Simulation results show that progressive performances of the proposed algorithm have a better convergence time.

• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.549-559
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• 1997

A multiply-connected network unsteady flow model for the main reach of the Han River is developed. It is a variable parameter model which allows variable roughness coefficient for each computational point according to the spatial position and the value of discharge. Sensitivities of the model to roughness coefficient and weir-flow discharge coefficient are tested, and as a result Manning's roughness coefficient is selected as the calibration parameter. The model is calibrated and verified using the records of the past flood events. A modified Gauss-Newton method is used for the optimal calibration of roughness coefficients. From the calibration of variable parameter model, spatial variation and discharge dependence of Manning's roughness coefficient are identified. That is, the roughness coefficient is higher for the upstream reach of the Wangsook stream Junction, and it decreases as the discharge increases. It turns out through the verification that the stages calculated by the variable parameter model agree better with the observed than those by the conventional single parameter model. Spatial variation of the roughness coefficient appears to be more significant than the dependence of the discharge.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.43-45
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• 2000

Traditionally, load flows have been calculated using the Gauss-Seidel and Newton-Raphson Method. DistFlow Method which is proposed by Wu and Baran is superior to the other two methods because it does not require the admittance matrix calculation to optimize the distribution system. This paper introduces a new alternative algorithm to the DistFlow Method which is slow and complex to find solutions as the number of lateral and sublateral increases. The proposed load flow method can construct System Jacobian easily. We can minimize the off-diagonal elements of the branch Jacobian and submatrices in the System Jacobian. Simulation results show that progressive performances of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.12
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• pp.2527-2533
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• 2011

In this paper we propose a new pre-processing algorithm applied to multi-view video coding using color compensation algorithm based on image features. Multi-view images have a difference between neighboring frames according to illumination and different camera characteristics. To compensate this color difference, first we model the characteristics of cameras based on frame's feature from each camera and then correct the color difference. To extract corresponding features from each frame, we use Harris corner detection algorithm and characteristic coefficients used in the model is estimated by using Gauss-Newton algorithm. In this algorithm, we compensate RGB components of target images, separately from the reference image. The experimental results with many test images show that the proposed algorithm peformed better than the histogram based algorithm as much as 14 % of bit reduction and 0.5 dB ~ 0.8dB of PSNR enhancement.